The brain's remarkable ability to recognize and remember objects depends on a series of visual processing stages culminating in inferotemporal cortex (IT). As the highest purely visual processing stage, IT contains dedicated domains for processing specific object classes, such as faces. Little is known, however, about the detailed organization and properties of neurons within these domains. The goal of this proposal is to provide such information by precisely targeting neural recordings to face and object selective regions of IT. An integrated system will be developed that uses fMRI to localize regions of interest and a novel x-ray based technique to return neural coordinates within these regions. Our first aim will be to measure the selectivity and tolerance properties of neurons throughout the 3D extent of an fMRI defined object patch. Different hypotheses about fine scale organization will be tested, and the underlying selectivity of neural populations compared to selectivity measured by fMRI. The second aim of our proposal will compare the organization in a face patch with a patch for novel objects. Face selective cells are already known to exist in face patches, but the question to be addressed is how the number, organization, or strength of tuning of cells in face patches differs from that in regions selective to unfamiliar objects. Such information will provide insights into how IT is organized across objects and whether strong familiarity with objects like faces refines neural maps. By bridging the gap between human fMRI and underlying neural structures, this work directly impacts our understanding of human object selective cortex. In case of loss of visual function, object level domains at the interface of memory and perception are prime targets for visual neural prosthetics. Knowledge of their precise locations and structures will guide repair and lay groundwork for the development of next-generation prosthetics.